earticle

영어

There have been active researches on the prediction of future events with moving (first person view) cameras by using deep-learning approaches. In many those approaches, the moving camera motion was considered as an important cue in future object localization and anticipation of traffic accidents. This paper argues that the moving cameramotion (i.e., ego-motion) is not necessary for these tasks because only the relative motion of the surrounding objects with respect to the moving camera is sufficient for those tasks. In this paper, we will present some empirical evidence from the recently published papers with codes and datasets. Comparison results with and without camera-motion shows that performance differences are rather minor. This may recommend not to use the camera-motion for reducing memories as well as inference time at edge devices because the number of parameters in the architecture can be significantly reduced.